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Mar 1 (Tue) @ 10:00am: "Brain-inspired Device-circuits-algorithm Co-design for Resource-constrained Hardware on the Edge," Melika Payvand, Sr. Research Scientist, UZH & ETH Zurich

Date and Time
Location
Zoom Meeting -

https://ucsb.zoom.us/j/86985215851

Abstract

As Artificial Intelligence (AI) becomes an increasingly integrated part of our daily lives, our digital society is shifting to an era of pervasive specialized "edge-computing" systems for a wide variety of tasks. The stringent memory and power budgets at the edge of the sensors have been fueling the advances in AI accelerators, whose precision reduction and sparsity exploitation techniques are in agreement with the solutions found by the ‘natural intelligent’ systems through millions of years of evolution.

Neuromorphic technologies aim to take further inspiration from the organizing principles of biological brains as a natural next step towards low power intelligent edge devices. The advances in emerging memory technologies augments this opportunity in terms of area and power efficiency. Simultaneously, significant progress is being made with new neuroscientific discoveries and machine learning insights inching us closer to understanding the efficiency of natural intelligent systems.

In this talk, I will go over a variety of design methodologies that we have developed for closing the gap between the new trends in devices, circuits, and algorithms, using a holistic approach, which is the foundation towards low-power real-time learning and processing on the edge.

Bio

Melika Payvand is a senior research scientist at the Institute of Neuroinformatics, University of Zurich and ETH Zurich. She received her M.S. and Ph.D. degrees in electrical and computer engineering from the University of California Santa Barbara in 2012 and 2016 respectively. Her research interest is in understanding the organizing principles of biological nervous systems and employing them in building more efficient and intelligent artificial systems, following a co-design approach across devices, circuits and algorithms.

She is an active member of the neuromorphic community, co-coordinating the European NEUROTECH project, chairing the neuromorphic engineering track at the IEEE ISCAS conference, co-chairing the International Conference on Neuromorphic Systems (ICONS), and serving as a scientific committee member of the Capocaccia neuromorphic intelligence workshop.

She has also co-organized the Women in Circuits and Systems (WiCAS) event at the IEEE ICECS conference, and has served as the guest editor of Frontiers in Neuroscience and IOP journal of neuromorphic computing and engineering.  She is the winner of the best neuromorph award of the 2019 Telluride neuromorphic workshop.

Hosted by: ECE Computer Engineering

Submitted by: Libby Straight <libby@ece.ucsb.edu>